Results 121 to 130 of about 38,888 (250)

A New Implementation of Network GARCH Model for Stock Volatility and Co‐Volatility Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT Volatility clustering and spillovers are key features of financial time series with many cross‐sectional assets. While network analysis links similar or correlated stocks and helps trace volatility spillovers, contemporary multivariate ARCH‐GARCH formulations struggle to represent structured network dependence and remain parsimonious.
Peiyi Zhou
wiley   +1 more source

Is Stock Price Volatility A Risk? : An Evaluation Review [PDF]

International Journal of Management, Accounting and Economics, 2019
Price volatility presents the investor possibilities and opportunities to buy securities at cheap prices and then sell it when they are overpriced, resulting in a profit at the end of the day.
Rabia Qammar, Rana Zain-Ul-Abidin
doaj  

A Novel Text‐Based Framework for Forecasting Carbon Prices

Journal of Forecasting, EarlyView.
ABSTRACT This study proposes a text‐based framework for predicting EU carbon prices. Using weekly data from 2020 to 2024, we construct a multivariate dataset combining financial indicators, commodity prices, Google Trends measures, and news‐based sentiment extracted using FinBERT.
Christian Oliver Ewald, Yaoyu Li
wiley   +1 more source

Estimation of temporally aggregated multivariate GARCH models [PDF]

This paper investigates the performance of quasi maximum likelihood (QML) and nonlinear least squares (NLS) estimation applied to temporally aggregated GARCH models.Since these are known to be only weak GARCH, the conditional variance of the aggregated ...
Hafner, C.M., Rombouts, J.V.K.
core  

Beta Forecasting With Realized Beta Estimators and Machine Learning Algorithms

Journal of Forecasting, EarlyView.
ABSTRACT This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Higher levels of beta forecast accuracy are demonstrated, relative to other studies in the literature. These improvements are also highly significant, both statistically and economically.
Bao Doan, Dulani Jayasuriya, John B. Lee, Jonathan J. Reeves   +3 more
wiley   +1 more source

The Role of Variance Risk Premium in Derivative Pricing: Modeling, Estimation and Impact

Journal of Futures Markets, EarlyView.
ABSTRACT This paper estimates a model where variance risk premiums (VRP) is not fully explained by equity risk premiums (ERP). This separation can be detected thanks to a new breed of GARCH models with enough innovations to disconnect returns from variances. This type of risk‐neutralization is compatible with continuous‐time settings.
Marcos Escobar‐Anel, Lars Stentoft, Xize Ye   +2 more
wiley   +1 more source

MODELLING CONDITIONAL VOLATILITY AND ASYMMETRY IN GOLD FUTURES RETURNS [PDF]

Analele Universităţii Constantin Brâncuşi din Târgu Jiu : Seria Economie
This study investigates the time-varying volatility dynamics of Gold Futures (GCZ5) daily returns over a ten-year period (October 28, 2015, to October 28, 2025).
SHAHIL RAZA , AMAN SHREEVASTAVA, BHARAT KUMAR MEHER, RAMONA BIRAU , VIRGIL POPESCU , STEFAN MARGARITESCU , GABRIELA ANA MARIA LUPU (FILIP) , CRISTINA SULTĂNOIU (PĂTULARU)   +7 more
doaj  

BAYESIAN ESTIMATION OF THE GAUSSIAN MIXTURE GARCH MODEL [PDF]

In this paper, we perform Bayesian inference and prediction for a GARCH model where the innovations are assumed to follow a mixture of two Gaussian distributions.
María Concepcion Ausin, Pedro Galeano
core  

Brexit and Its Impact on EU Financial Markets

International Journal of Finance &Economics, EarlyView.
ABSTRACT We investigate the impact of Brexit on volatility spillovers across the EU countries. We introduce a Brexit intensity measure that assigns an intensity score reflective of the financial markets' reaction to the events that occurred as Brexit negotiations began to unfold.
Marwan Izzeldin, Gulnur Muradoglu, Vasileios Pappas, Sheeja Sivaprasad   +3 more
wiley   +1 more source

A Framework for Cryptocurrency Volatility Prediction Based on Cross-Correlation Analysis Using Deep Learning [PDF]

International Journal of Information and Communication Technology Research
The popularity of cryptocurrencies has intensified the need for accurate volatility prediction models. This research proposes a novel approach to enhance conditional variance predictions for cryptocurrencies.
Masoud Omidvari Abarghouie, Sasan H. Alizadeh, Ahmad khadem Zadeh, Abbas Koochari   +3 more
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